Over the last half century, the acquisition of a chromatogram has evolved from fraction collection, offline measurement and manual recording of discrete values, to a chart recorder providing a continuous analog trace, to digital acquisition of the detector response. Present chromatographic hardware/software systems allow fast facile quantitation using either area or height based approaches. As long as one is in a domain where the detector response is linearly proportional to the analyte (i.e., the substance to be separated during chromatography) concentration in the detection cell, the peak trace area is a true representation of the amount of the analyte passing through the detector.
Area and height based quantitation are validated chromatography methods—highly reliable, but often over a limited range. Typical practice involves a single standard linear regression equation covering multiple concentrations/amounts for quantitation. It is well known that while linear regression minimizes absolute errors, the relative error, often of greater importance, becomes very large at low analyte concentrations. Weighted linear regression provides a solution to this, but it is notably absent from popular chromatographic data handling software. Height is often regarded as more accurate than area, especially if peaks are not well resolved in the chromatogram. Height is less affected by asymmetry and overlap, and provides less quantitation error for peaks with limited overlap. In a survey of chromatographers, area was preferred over height for better accuracy and precision. However, poor resolution or significant peak asymmetry (the two are related: high asymmetry increases the probability of overlap) induces greater error in area-based quantitation. Both area and height are affected by detector non-linearity, and detector saturation leads to clipped peaks.
General height and area based approaches to quantitation have not changed since the inception of quantitative chromatography.